Laboratory and Field Assessments of Prey-Mediated Effects of Transgenic Bt Rice on <I>Ummeliata insecticeps</I> (Araneida: Linyphiidae)
Bibliographic record
Abstract
One major concern regarding the release of Bt rice is its potential impact through tritrophic interactions on nontarget arthropods, especially natural enemies. We studied the effects of two Bt transgenic rice varieties, TT9- 3 and KMD1, expressing Cry1Ab/Cry1Ac and Cry1Ab, respectively, on a predatory ground spider [Ummeliata insecticeps (Bösenberg et Strand)] supplied with Bt rice-fed brown planthopper [Nilaparvata lugens (Stål)] nymphs. Although immunoassays confirmed that U. insecticeps ingested Bt insecticidal protein when supplied with Bt rice-fed N. lugens, no negative effects were found on its survival and development. Furthermore, the fecundity of U. insecticeps fed prey reared on Bt rice was not significantly different from that of those fed prey reared on non-Bt rice. A 3-yr field trial indicated that Bt rice did not significantly affect the population density of U. insecticeps in comparison with non-Bt rice. In conclusion, the Bt rice lines tested in this study had no adverse effects on the survival, developmental time, or fecundity of U. insecticeps in the laboratory or on population dynamics in the field.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".